Overview

Brought to you by YData

Dataset statistics

Number of variables16
Number of observations5012
Missing cells0
Missing cells (%)0.0%
Duplicate rows3
Duplicate rows (%)0.1%
Total size in memory598.6 KiB
Average record size in memory122.3 B

Variable types

Categorical2
Numeric14

Alerts

Dataset has 3 (0.1%) duplicate rowsDuplicates
host_listings_minimum_nights is highly overall correlated with log_host_listings_count and 1 other fieldsHigh correlation
latitude is highly overall correlated with longitude and 1 other fieldsHigh correlation
log_host_listings_count is highly overall correlated with host_listings_minimum_nightsHigh correlation
log_minimum_nights is highly overall correlated with host_listings_minimum_nightsHigh correlation
log_number_of_reviews is highly overall correlated with log_reviews_per_monthHigh correlation
log_price is highly overall correlated with price and 3 other fieldsHigh correlation
log_reviews_per_month is highly overall correlated with log_number_of_reviewsHigh correlation
longitude is highly overall correlated with latitude and 1 other fieldsHigh correlation
neighbourhood is highly overall correlated with latitude and 1 other fieldsHigh correlation
price is highly overall correlated with log_price and 3 other fieldsHigh correlation
price^2 is highly overall correlated with log_price and 3 other fieldsHigh correlation
price^3 is highly overall correlated with log_price and 3 other fieldsHigh correlation
price^4 is highly overall correlated with log_price and 3 other fieldsHigh correlation
price^2 is highly skewed (γ1 = 25.38358231) Skewed
price^3 is highly skewed (γ1 = 34.81686362) Skewed
price^4 is highly skewed (γ1 = 39.25340936) Skewed
log_minimum_nights has 1521 (30.3%) zeros Zeros
log_host_listings_count has 2106 (42.0%) zeros Zeros
host_listings_minimum_nights has 3018 (60.2%) zeros Zeros

Reproduction

Analysis started2025-03-01 00:40:57.400980
Analysis finished2025-03-01 00:41:10.120476
Duration12.72 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

neighbourhood
Categorical

High correlation 

Distinct30
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size45.3 KiB
West Town
566 
Near North Side
532 
infrequent
528 
Lake View
418 
Logan Square
299 
Other values (25)
2669 

Length

Max length18
Median length14
Mean length10.851157
Min length4

Characters and Unicode

Total characters54386
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowinfrequent
2nd rowNorth Center
3rd rowLogan Square
4th rowRogers Park
5th rowSouth Shore

Common Values

ValueCountFrequency (%)
West Town 566
 
11.3%
Near North Side 532
 
10.6%
infrequent 528
 
10.5%
Lake View 418
 
8.3%
Logan Square 299
 
6.0%
Loop 287
 
5.7%
Lincoln Park 259
 
5.2%
Near West Side 258
 
5.1%
Lower West Side 153
 
3.1%
Edgewater 137
 
2.7%
Other values (20) 1575
31.4%

Length

2025-03-01T09:41:10.164315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
side 1057
 
10.9%
west 1032
 
10.6%
near 904
 
9.3%
park 793
 
8.2%
north 644
 
6.6%
town 566
 
5.8%
infrequent 528
 
5.4%
lake 418
 
4.3%
view 418
 
4.3%
square 417
 
4.3%
Other values (26) 2932
30.2%

Most occurring characters

ValueCountFrequency (%)
e 6686
 
12.3%
4697
 
8.6%
r 4576
 
8.4%
o 3679
 
6.8%
a 3602
 
6.6%
n 3286
 
6.0%
t 3094
 
5.7%
i 2717
 
5.0%
d 1871
 
3.4%
S 1736
 
3.2%
Other values (31) 18442
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 54386
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 6686
 
12.3%
4697
 
8.6%
r 4576
 
8.4%
o 3679
 
6.8%
a 3602
 
6.6%
n 3286
 
6.0%
t 3094
 
5.7%
i 2717
 
5.0%
d 1871
 
3.4%
S 1736
 
3.2%
Other values (31) 18442
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 54386
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 6686
 
12.3%
4697
 
8.6%
r 4576
 
8.4%
o 3679
 
6.8%
a 3602
 
6.6%
n 3286
 
6.0%
t 3094
 
5.7%
i 2717
 
5.0%
d 1871
 
3.4%
S 1736
 
3.2%
Other values (31) 18442
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 54386
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 6686
 
12.3%
4697
 
8.6%
r 4576
 
8.4%
o 3679
 
6.8%
a 3602
 
6.6%
n 3286
 
6.0%
t 3094
 
5.7%
i 2717
 
5.0%
d 1871
 
3.4%
S 1736
 
3.2%
Other values (31) 18442
33.9%

latitude
Real number (ℝ)

High correlation 

Distinct4226
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.899279
Minimum41.64736
Maximum42.02251
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:10.225633image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum41.64736
5-th percentile41.782967
Q141.873238
median41.901885
Q341.939765
95-th percentile41.988189
Maximum42.02251
Range0.37515
Interquartile range (IQR)0.0665275

Descriptive statistics

Standard deviation0.058870345
Coefficient of variation (CV)0.0014050443
Kurtosis0.79813379
Mean41.899279
Median Absolute Deviation (MAD)0.0344
Skewness-0.72376333
Sum209999.19
Variance0.0034657175
MonotonicityNot monotonic
2025-03-01T09:41:10.704798image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.88306 19
 
0.4%
41.89111 15
 
0.3%
41.88608 14
 
0.3%
41.89063 13
 
0.3%
41.88558 11
 
0.2%
41.92819 11
 
0.2%
41.89862 8
 
0.2%
41.88652 7
 
0.1%
42.01653 7
 
0.1%
41.89235 7
 
0.1%
Other values (4216) 4900
97.8%
ValueCountFrequency (%)
41.64736 1
< 0.1%
41.65208 1
< 0.1%
41.65388 1
< 0.1%
41.65578 1
< 0.1%
41.65977 1
< 0.1%
41.68289 1
< 0.1%
41.68612 1
< 0.1%
41.6883 1
< 0.1%
41.68906 1
< 0.1%
41.68909 1
< 0.1%
ValueCountFrequency (%)
42.02251 1
< 0.1%
42.02139 1
< 0.1%
42.02119 1
< 0.1%
42.02105 1
< 0.1%
42.02087 1
< 0.1%
42.02077 1
< 0.1%
42.02042 1
< 0.1%
42.01957 1
< 0.1%
42.01947 1
< 0.1%
42.01926 1
< 0.1%

longitude
Real number (ℝ)

High correlation 

Distinct4036
Distinct (%)80.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-87.664064
Minimum-87.84681
Maximum-87.53752
Zeros0
Zeros (%)0.0%
Negative5012
Negative (%)100.0%
Memory size78.3 KiB
2025-03-01T09:41:10.774457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-87.84681
5-th percentile-87.736168
Q1-87.686782
median-87.660935
Q3-87.633365
95-th percentile-87.604236
Maximum-87.53752
Range0.30929
Interquartile range (IQR)0.0534175

Descriptive statistics

Standard deviation0.042663199
Coefficient of variation (CV)-0.00048666692
Kurtosis1.2919833
Mean-87.664064
Median Absolute Deviation (MAD)0.02703
Skewness-0.67734759
Sum-439372.29
Variance0.0018201486
MonotonicityNot monotonic
2025-03-01T09:41:10.844560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-87.65131 17
 
0.3%
-87.63422 15
 
0.3%
-87.62205 15
 
0.3%
-87.61903 14
 
0.3%
-87.6525 13
 
0.3%
-87.6257 12
 
0.2%
-87.62797 8
 
0.2%
-87.62472 7
 
0.1%
-87.62732 7
 
0.1%
-87.65159 7
 
0.1%
Other values (4026) 4897
97.7%
ValueCountFrequency (%)
-87.84681 1
< 0.1%
-87.84527 1
< 0.1%
-87.84474 1
< 0.1%
-87.84363 1
< 0.1%
-87.84196 1
< 0.1%
-87.84193 1
< 0.1%
-87.84012 1
< 0.1%
-87.83983 1
< 0.1%
-87.83528 1
< 0.1%
-87.83526 2
< 0.1%
ValueCountFrequency (%)
-87.53752 1
< 0.1%
-87.5379 1
< 0.1%
-87.54496 1
< 0.1%
-87.54557 1
< 0.1%
-87.54593 1
< 0.1%
-87.54595 1
< 0.1%
-87.54596 2
< 0.1%
-87.54603 1
< 0.1%
-87.54615 1
< 0.1%
-87.54775 1
< 0.1%

room_type
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size44.2 KiB
Entire home/apt
3447 
Private room
1441 
Shared room
 
72
Hotel room
 
52

Length

Max length15
Median length15
Mean length14.028132
Min length10

Characters and Unicode

Total characters70309
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPrivate room
2nd rowEntire home/apt
3rd rowEntire home/apt
4th rowEntire home/apt
5th rowPrivate room

Common Values

ValueCountFrequency (%)
Entire home/apt 3447
68.8%
Private room 1441
28.8%
Shared room 72
 
1.4%
Hotel room 52
 
1.0%

Length

2025-03-01T09:41:10.908441image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-03-01T09:41:10.947978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
entire 3447
34.4%
home/apt 3447
34.4%
room 1565
15.6%
private 1441
14.4%
shared 72
 
0.7%
hotel 52
 
0.5%

Most occurring characters

ValueCountFrequency (%)
e 8459
12.0%
t 8387
11.9%
o 6629
9.4%
r 6525
9.3%
5012
 
7.1%
m 5012
 
7.1%
a 4960
 
7.1%
i 4888
 
7.0%
h 3519
 
5.0%
n 3447
 
4.9%
Other values (9) 13471
19.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70309
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 8459
12.0%
t 8387
11.9%
o 6629
9.4%
r 6525
9.3%
5012
 
7.1%
m 5012
 
7.1%
a 4960
 
7.1%
i 4888
 
7.0%
h 3519
 
5.0%
n 3447
 
4.9%
Other values (9) 13471
19.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70309
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 8459
12.0%
t 8387
11.9%
o 6629
9.4%
r 6525
9.3%
5012
 
7.1%
m 5012
 
7.1%
a 4960
 
7.1%
i 4888
 
7.0%
h 3519
 
5.0%
n 3447
 
4.9%
Other values (9) 13471
19.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70309
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 8459
12.0%
t 8387
11.9%
o 6629
9.4%
r 6525
9.3%
5012
 
7.1%
m 5012
 
7.1%
a 4960
 
7.1%
i 4888
 
7.0%
h 3519
 
5.0%
n 3447
 
4.9%
Other values (9) 13471
19.2%

price
Real number (ℝ)

High correlation 

Distinct448
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.92877
Minimum14
Maximum3429
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:11.004218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile31
Q165
median99
Q3155
95-th percentile393
Maximum3429
Range3415
Interquartile range (IQR)90

Descriptive statistics

Standard deviation165.88465
Coefficient of variation (CV)1.1854935
Kurtosis98.503701
Mean139.92877
Median Absolute Deviation (MAD)43
Skewness7.4755277
Sum701323
Variance27517.716
MonotonicityNot monotonic
2025-03-01T09:41:11.071821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
50 110
 
2.2%
80 101
 
2.0%
75 99
 
2.0%
150 97
 
1.9%
100 88
 
1.8%
65 87
 
1.7%
70 84
 
1.7%
60 77
 
1.5%
90 76
 
1.5%
55 73
 
1.5%
Other values (438) 4120
82.2%
ValueCountFrequency (%)
14 2
 
< 0.1%
15 6
0.1%
16 2
 
< 0.1%
17 2
 
< 0.1%
18 4
 
0.1%
19 4
 
0.1%
20 8
0.2%
21 9
0.2%
22 11
0.2%
23 6
0.1%
ValueCountFrequency (%)
3429 1
 
< 0.1%
3070 1
 
< 0.1%
3000 1
 
< 0.1%
2788 1
 
< 0.1%
1999 1
 
< 0.1%
1921 1
 
< 0.1%
1828 1
 
< 0.1%
1500 3
0.1%
1499 1
 
< 0.1%
1400 1
 
< 0.1%
Distinct675
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.7741487
Minimum-1
Maximum3.38616
Zeros0
Zeros (%)0.0%
Negative877
Negative (%)17.5%
Memory size78.3 KiB
2025-03-01T09:41:11.139818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q12.0417873
median2.1646502
Q32.5052857
95-th percentile2.9047696
Maximum3.38616
Range4.38616
Interquartile range (IQR)0.46349836

Descriptive statistics

Standard deviation1.3060209
Coefficient of variation (CV)0.73613947
Kurtosis0.6702304
Mean1.7741487
Median Absolute Deviation (MAD)0.30088134
Skewness-1.5376373
Sum8892.0331
Variance1.7056905
MonotonicityNot monotonic
2025-03-01T09:41:11.218407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 877
 
17.5%
2.06483222 157
 
3.1%
2.041787319 134
 
2.7%
2.465531557 120
 
2.4%
2.068556895 108
 
2.2%
2.505285674 81
 
1.6%
2.037824751 79
 
1.6%
2.090258053 76
 
1.5%
2.013258665 75
 
1.5%
2.093771781 68
 
1.4%
Other values (665) 3237
64.6%
ValueCountFrequency (%)
-1 877
17.5%
2.009025742 2
 
< 0.1%
2.013258665 75
 
1.5%
2.01745073 36
 
0.7%
2.021602716 36
 
0.7%
2.025715384 42
 
0.8%
2.029789471 39
 
0.8%
2.033825694 42
 
0.8%
2.037824751 79
 
1.6%
2.041787319 134
 
2.7%
ValueCountFrequency (%)
3.386159959 1
< 0.1%
3.374216605 1
< 0.1%
3.363066419 1
< 0.1%
3.356618542 1
< 0.1%
3.337479228 1
< 0.1%
3.311351158 1
< 0.1%
3.309864283 1
< 0.1%
3.300182295 1
< 0.1%
3.299311135 1
< 0.1%
3.296028636 1
< 0.1%

log_reviews_per_month
Real number (ℝ)

High correlation 

Distinct628
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-0.11839046
Minimum-1
Maximum1.5122841
Zeros15
Zeros (%)0.3%
Negative2555
Negative (%)51.0%
Memory size78.3 KiB
2025-03-01T09:41:11.287602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q1-0.60205999
median-0.022276395
Q30.36735592
95-th percentile0.67742064
Maximum1.5122841
Range2.5122841
Interquartile range (IQR)0.96941591

Descriptive statistics

Standard deviation0.5724843
Coefficient of variation (CV)-4.8355609
Kurtosis-1.1864983
Mean-0.11839046
Median Absolute Deviation (MAD)0.45920967
Skewness-0.23456376
Sum-593.37301
Variance0.32773827
MonotonicityNot monotonic
2025-03-01T09:41:11.364570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 877
 
17.5%
0.04139268516 59
 
1.2%
-0.5686362358 48
 
1.0%
-0.6197887583 43
 
0.9%
-0.7447274949 41
 
0.8%
-0.585026652 36
 
0.7%
-0.721246399 33
 
0.7%
-0.8860566477 32
 
0.6%
-0.6575773192 32
 
0.6%
-0.4948500217 31
 
0.6%
Other values (618) 3780
75.4%
ValueCountFrequency (%)
-1 877
17.5%
-0.920818754 12
 
0.2%
-0.8860566477 32
 
0.6%
-0.8538719643 27
 
0.5%
-0.8239087409 18
 
0.4%
-0.7958800173 23
 
0.5%
-0.7695510786 22
 
0.4%
-0.7447274949 41
 
0.8%
-0.721246399 33
 
0.7%
-0.6989700043 23
 
0.5%
ValueCountFrequency (%)
1.512284063 1
< 0.1%
1.231214648 1
< 0.1%
1.071513805 1
< 0.1%
1.06595298 1
< 0.1%
1.051152522 1
< 0.1%
1.048053173 1
< 0.1%
1.044147621 1
< 0.1%
1.039810554 1
< 0.1%
1.025715384 1
< 0.1%
0.983175072 1
< 0.1%

log_number_of_reviews
Real number (ℝ)

High correlation 

Distinct308
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.90284451
Minimum-1
Maximum2.8007858
Zeros0
Zeros (%)0.0%
Negative877
Negative (%)17.5%
Memory size78.3 KiB
2025-03-01T09:41:11.445743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q10.32221929
median1.1789769
Q31.7411516
95-th percentile2.2407988
Maximum2.8007858
Range3.8007858
Interquartile range (IQR)1.4189323

Descriptive statistics

Standard deviation1.068376
Coefficient of variation (CV)1.1833444
Kurtosis-0.75978922
Mean0.90284451
Median Absolute Deviation (MAD)0.68761525
Skewness-0.63728601
Sum4525.0567
Variance1.1414273
MonotonicityNot monotonic
2025-03-01T09:41:11.519283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-1 877
 
17.5%
0.04139268516 326
 
6.5%
0.3222192947 225
 
4.5%
0.4913616938 185
 
3.7%
0.7075701761 117
 
2.3%
0.6127838567 117
 
2.3%
0.8512583487 102
 
2.0%
0.785329835 83
 
1.7%
0.9590413923 78
 
1.6%
0.9084850189 75
 
1.5%
Other values (298) 2827
56.4%
ValueCountFrequency (%)
-1 877
17.5%
0.04139268516 326
 
6.5%
0.3222192947 225
 
4.5%
0.4913616938 185
 
3.7%
0.6127838567 117
 
2.3%
0.7075701761 117
 
2.3%
0.785329835 83
 
1.7%
0.8512583487 102
 
2.0%
0.9084850189 75
 
1.5%
0.9590413923 78
 
1.6%
ValueCountFrequency (%)
2.80078579 1
< 0.1%
2.795949499 1
< 0.1%
2.733277534 1
< 0.1%
2.708505881 1
< 0.1%
2.704236337 1
< 0.1%
2.699056855 1
< 0.1%
2.69818757 2
< 0.1%
2.688508808 1
< 0.1%
2.663795122 1
< 0.1%
2.645520515 1
< 0.1%

log_price
Real number (ℝ)

High correlation 

Distinct448
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0112387
Minimum1.146128
Maximum3.5351675
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:11.587527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1.146128
5-th percentile1.4913617
Q11.8129134
median1.9956352
Q32.1903317
95-th percentile2.5943926
Maximum3.5351675
Range2.3890394
Interquartile range (IQR)0.37741834

Descriptive statistics

Standard deviation0.31855437
Coefficient of variation (CV)0.15838715
Kurtosis0.75905852
Mean2.0112387
Median Absolute Deviation (MAD)0.18945522
Skewness0.45091562
Sum10080.328
Variance0.10147688
MonotonicityNot monotonic
2025-03-01T09:41:11.666236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.698970004 110
 
2.2%
1.903089987 101
 
2.0%
1.875061263 99
 
2.0%
2.176091259 97
 
1.9%
2 88
 
1.8%
1.812913357 87
 
1.7%
1.84509804 84
 
1.7%
1.77815125 77
 
1.5%
1.954242509 76
 
1.5%
1.740362689 73
 
1.5%
Other values (438) 4120
82.2%
ValueCountFrequency (%)
1.146128036 2
 
< 0.1%
1.176091259 6
0.1%
1.204119983 2
 
< 0.1%
1.230448921 2
 
< 0.1%
1.255272505 4
 
0.1%
1.278753601 4
 
0.1%
1.301029996 8
0.2%
1.322219295 9
0.2%
1.342422681 11
0.2%
1.361727836 6
0.1%
ValueCountFrequency (%)
3.535167485 1
 
< 0.1%
3.487138375 1
 
< 0.1%
3.477121255 1
 
< 0.1%
3.445292769 1
 
< 0.1%
3.300812794 1
 
< 0.1%
3.283527365 1
 
< 0.1%
3.261976191 1
 
< 0.1%
3.176091259 3
0.1%
3.175801633 1
 
< 0.1%
3.146128036 1
 
< 0.1%

log_minimum_nights
Real number (ℝ)

High correlation  Zeros 

Distinct48
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.45549834
Minimum0
Maximum2.2552725
Zeros1521
Zeros (%)30.3%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:11.749006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.30103
Q30.47712125
95-th percentile1.4913617
Maximum2.2552725
Range2.2552725
Interquartile range (IQR)0.47712125

Descriptive statistics

Standard deviation0.50270629
Coefficient of variation (CV)1.1036402
Kurtosis0.65635319
Mean0.45549834
Median Absolute Deviation (MAD)0.30103
Skewness1.2988705
Sum2282.9577
Variance0.25271361
MonotonicityNot monotonic
2025-03-01T09:41:11.831587image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0.3010299957 1628
32.5%
0 1521
30.3%
0.4771212547 685
13.7%
1.477121255 289
 
5.8%
0.6020599913 135
 
2.7%
1.491361694 109
 
2.2%
0.84509804 104
 
2.1%
1.505149978 87
 
1.7%
0.6989700043 85
 
1.7%
1.146128036 56
 
1.1%
Other values (38) 313
 
6.2%
ValueCountFrequency (%)
0 1521
30.3%
0.3010299957 1628
32.5%
0.4771212547 685
13.7%
0.6020599913 135
 
2.7%
0.6989700043 85
 
1.7%
0.7781512504 25
 
0.5%
0.84509804 104
 
2.1%
0.903089987 1
 
< 0.1%
0.9542425094 1
 
< 0.1%
1 33
 
0.7%
ValueCountFrequency (%)
2.255272505 7
0.1%
2.252853031 1
 
< 0.1%
2.176091259 1
 
< 0.1%
2.146128036 1
 
< 0.1%
2.079181246 4
 
0.1%
2 1
 
< 0.1%
1.959041392 2
 
< 0.1%
1.954242509 14
0.3%
1.944482672 1
 
< 0.1%
1.908485019 1
 
< 0.1%

log_host_listings_count
Real number (ℝ)

High correlation  Zeros 

Distinct33
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.51731125
Minimum0
Maximum2.3117539
Zeros2106
Zeros (%)42.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:11.900176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.30103
Q30.84509804
95-th percentile1.7923917
Maximum2.3117539
Range2.3117539
Interquartile range (IQR)0.84509804

Descriptive statistics

Standard deviation0.61568158
Coefficient of variation (CV)1.190157
Kurtosis0.62131458
Mean0.51731125
Median Absolute Deviation (MAD)0.30103
Skewness1.1861676
Sum2592.764
Variance0.37906381
MonotonicityNot monotonic
2025-03-01T09:41:11.959545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
0 2106
42.0%
0.3010299957 674
 
13.4%
0.4771212547 349
 
7.0%
0.6020599913 296
 
5.9%
2.311753861 156
 
3.1%
0.6989700043 149
 
3.0%
0.7781512504 102
 
2.0%
0.84509804 101
 
2.0%
0.9542425094 94
 
1.9%
0.903089987 77
 
1.5%
Other values (23) 908
18.1%
ValueCountFrequency (%)
0 2106
42.0%
0.3010299957 674
 
13.4%
0.4771212547 349
 
7.0%
0.6020599913 296
 
5.9%
0.6989700043 149
 
3.0%
0.7781512504 102
 
2.0%
0.84509804 101
 
2.0%
0.903089987 77
 
1.5%
0.9542425094 94
 
1.9%
1 58
 
1.2%
ValueCountFrequency (%)
2.311753861 156
3.1%
1.86332286 57
 
1.1%
1.792391689 52
 
1.0%
1.672097858 75
1.5%
1.653212514 36
 
0.7%
1.643452676 36
 
0.7%
1.568201724 31
 
0.6%
1.491361694 52
 
1.0%
1.477121255 24
 
0.5%
1.447158031 27
 
0.5%

log_nights_booked
Real number (ℝ)

Distinct361
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8789671
Minimum-1
Maximum2.5624118
Zeros0
Zeros (%)0.0%
Negative286
Negative (%)5.7%
Memory size78.3 KiB
2025-03-01T09:41:12.023390image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-1
5-th percentile-1
Q11.5575072
median2.314078
Q32.5199592
95-th percentile2.5624118
Maximum2.5624118
Range3.5624118
Interquartile range (IQR)0.96245198

Descriptive statistics

Standard deviation0.94971217
Coefficient of variation (CV)0.50544375
Kurtosis2.4930296
Mean1.8789671
Median Absolute Deviation (MAD)0.24833384
Skewness-1.7945892
Sum9417.383
Variance0.90195321
MonotonicityNot monotonic
2025-03-01T09:41:12.103282image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.562411833 942
 
18.8%
-1 286
 
5.7%
0.04139268516 127
 
2.5%
2.43949059 87
 
1.7%
2.441066407 75
 
1.5%
2.009025742 70
 
1.4%
2.269746373 62
 
1.2%
1.004321374 57
 
1.1%
2.267406419 57
 
1.1%
0.3222192947 51
 
1.0%
Other values (351) 3198
63.8%
ValueCountFrequency (%)
-1 286
5.7%
0.04139268516 127
2.5%
0.3222192947 51
 
1.0%
0.4913616938 50
 
1.0%
0.6127838567 28
 
0.6%
0.7075701761 49
 
1.0%
0.785329835 36
 
0.7%
0.8512583487 29
 
0.6%
0.9084850189 21
 
0.4%
0.9590413923 22
 
0.4%
ValueCountFrequency (%)
2.562411833 942
18.8%
2.561220679 43
 
0.9%
2.560026249 10
 
0.2%
2.558828525 22
 
0.4%
2.557627488 15
 
0.3%
2.556423121 8
 
0.2%
2.555215405 10
 
0.2%
2.554004321 12
 
0.2%
2.55278985 4
 
0.1%
2.551571974 7
 
0.1%

host_listings_minimum_nights
Real number (ℝ)

High correlation  Zeros 

Distinct173
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.34913936
Minimum0
Maximum3.6413847
Zeros3018
Zeros (%)60.2%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:12.175763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30.23424687
95-th percentile2.4545485
Maximum3.6413847
Range3.6413847
Interquartile range (IQR)0.23424687

Descriptive statistics

Standard deviation0.7858197
Coefficient of variation (CV)2.2507336
Kurtosis7.0928592
Mean0.34913936
Median Absolute Deviation (MAD)0
Skewness2.8090607
Sum1749.8865
Variance0.6175126
MonotonicityNot monotonic
2025-03-01T09:41:12.276524image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3018
60.2%
0.09061905829 242
 
4.8%
0.1436278092 223
 
4.4%
3.414740764 156
 
3.1%
0.1812381166 134
 
2.7%
0.2276446917 75
 
1.5%
0.2104109374 60
 
1.2%
0.2543998593 48
 
1.0%
0.2872556185 43
 
0.9%
0.5033516109 39
 
0.8%
Other values (163) 974
 
19.4%
ValueCountFrequency (%)
0 3018
60.2%
0.09061905829 242
 
4.8%
0.1436278092 223
 
4.4%
0.1812381166 134
 
2.7%
0.2104109374 60
 
1.2%
0.2276446917 75
 
1.5%
0.2342468675 36
 
0.7%
0.2543998593 48
 
1.0%
0.2718571749 14
 
0.3%
0.2872556185 43
 
0.9%
ValueCountFrequency (%)
3.641384742 1
 
< 0.1%
3.414740764 156
3.1%
3.313269874 20
 
0.4%
2.976064695 1
 
< 0.1%
2.804580363 5
 
0.1%
2.778888337 24
 
0.5%
2.752353801 4
 
0.1%
2.72491962 1
 
< 0.1%
2.696522642 1
 
< 0.1%
2.495605799 36
 
0.7%

price^2
Real number (ℝ)

High correlation  Skewed 

Distinct448
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47092.287
Minimum196
Maximum11758041
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:12.359852image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum196
5-th percentile961
Q14225
median9801
Q324025
95-th percentile154449
Maximum11758041
Range11757845
Interquartile range (IQR)19800

Descriptive statistics

Standard deviation311866.53
Coefficient of variation (CV)6.6224545
Kurtosis783.44525
Mean47092.287
Median Absolute Deviation (MAD)7301
Skewness25.383582
Sum2.3602654 × 108
Variance9.7260731 × 1010
MonotonicityNot monotonic
2025-03-01T09:41:12.447218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2500 110
 
2.2%
6400 101
 
2.0%
5625 99
 
2.0%
22500 97
 
1.9%
10000 88
 
1.8%
4225 87
 
1.7%
4900 84
 
1.7%
3600 77
 
1.5%
8100 76
 
1.5%
3025 73
 
1.5%
Other values (438) 4120
82.2%
ValueCountFrequency (%)
196 2
 
< 0.1%
225 6
0.1%
256 2
 
< 0.1%
289 2
 
< 0.1%
324 4
 
0.1%
361 4
 
0.1%
400 8
0.2%
441 9
0.2%
484 11
0.2%
529 6
0.1%
ValueCountFrequency (%)
11758041 1
 
< 0.1%
9424900 1
 
< 0.1%
9000000 1
 
< 0.1%
7772944 1
 
< 0.1%
3996001 1
 
< 0.1%
3690241 1
 
< 0.1%
3341584 1
 
< 0.1%
2250000 3
0.1%
2247001 1
 
< 0.1%
1960000 1
 
< 0.1%

price^3
Real number (ℝ)

High correlation  Skewed 

Distinct448
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48392686
Minimum2744
Maximum4.0318323 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:12.521851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum2744
5-th percentile29791
Q1274625
median970299
Q33723875
95-th percentile60698457
Maximum4.0318323 × 1010
Range4.031832 × 1010
Interquartile range (IQR)3449250

Descriptive statistics

Standard deviation8.8382109 × 108
Coefficient of variation (CV)18.263526
Kurtosis1333.1992
Mean48392686
Median Absolute Deviation (MAD)879174
Skewness34.816864
Sum2.4254414 × 1011
Variance7.8113971 × 1017
MonotonicityNot monotonic
2025-03-01T09:41:12.601115image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
125000 110
 
2.2%
512000 101
 
2.0%
421875 99
 
2.0%
3375000 97
 
1.9%
1000000 88
 
1.8%
274625 87
 
1.7%
343000 84
 
1.7%
216000 77
 
1.5%
729000 76
 
1.5%
166375 73
 
1.5%
Other values (438) 4120
82.2%
ValueCountFrequency (%)
2744 2
 
< 0.1%
3375 6
0.1%
4096 2
 
< 0.1%
4913 2
 
< 0.1%
5832 4
 
0.1%
6859 4
 
0.1%
8000 8
0.2%
9261 9
0.2%
10648 11
0.2%
12167 6
0.1%
ValueCountFrequency (%)
4.031832259 × 10101
 
< 0.1%
2.8934443 × 10101
 
< 0.1%
2.7 × 10101
 
< 0.1%
2.167096787 × 10101
 
< 0.1%
7988005999 1
 
< 0.1%
7088952961 1
 
< 0.1%
6108415552 1
 
< 0.1%
3375000000 3
0.1%
3368254499 1
 
< 0.1%
2744000000 1
 
< 0.1%

price^4
Real number (ℝ)

High correlation  Skewed 

Distinct448
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9459009 × 1010
Minimum38416
Maximum1.3825153 × 1014
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size78.3 KiB
2025-03-01T09:41:12.674671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum38416
5-th percentile923521
Q117850625
median96059601
Q35.7720062 × 108
95-th percentile2.3854494 × 1010
Maximum1.3825153 × 1014
Range1.3825153 × 1014
Interquartile range (IQR)5.5935 × 108

Descriptive statistics

Standard deviation2.7508166 × 1012
Coefficient of variation (CV)27.657792
Kurtosis1680.4379
Mean9.9459009 × 1010
Median Absolute Deviation (MAD)93499601
Skewness39.253409
Sum4.9848855 × 1014
Variance7.5669921 × 1024
MonotonicityNot monotonic
2025-03-01T09:41:12.753358image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6250000 110
 
2.2%
40960000 101
 
2.0%
31640625 99
 
2.0%
506250000 97
 
1.9%
100000000 88
 
1.8%
17850625 87
 
1.7%
24010000 84
 
1.7%
12960000 77
 
1.5%
65610000 76
 
1.5%
9150625 73
 
1.5%
Other values (438) 4120
82.2%
ValueCountFrequency (%)
38416 2
 
< 0.1%
50625 6
0.1%
65536 2
 
< 0.1%
83521 2
 
< 0.1%
104976 4
 
0.1%
130321 4
 
0.1%
160000 8
0.2%
194481 9
0.2%
234256 11
0.2%
279841 6
0.1%
ValueCountFrequency (%)
1.382515282 × 10141
 
< 0.1%
8.882874001 × 10131
 
< 0.1%
8.1 × 10131
 
< 0.1%
6.041865843 × 10131
 
< 0.1%
1.596802399 × 10131
 
< 0.1%
1.361787864 × 10131
 
< 0.1%
1.116618363 × 10131
 
< 0.1%
5.0625 × 10123
0.1%
5.049013494 × 10121
 
< 0.1%
3.8416 × 10121
 
< 0.1%

Interactions

2025-03-01T09:41:09.156186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:57.731335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.535984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.535707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.348288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.308338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.103458image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.983408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.002903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.723751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.501698image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.318294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.492626image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.300085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.213703image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:57.791296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.603688image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.596371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.407934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.370112image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.162424image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.044059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.056285image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.777754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.561308image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.381480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.547318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.368419image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.271216image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:57.851763image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.675207image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.654402image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.462148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.440704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.222030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.103516image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.108504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.831090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.619056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.442914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.602351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.434671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.327265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:57.909902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.738126image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.713870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.516966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.495114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.280860image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.155789image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.161238image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.885284image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.677745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.835896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.660288image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.498349image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.380629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:57.963345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.791678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.771448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.565308image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.546271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.335909image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.206206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.209773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.947256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.736142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.891171image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.717173image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.555879image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.435220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.018745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.845000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.830640image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.617297image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.596339image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.396365image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.257184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.259883image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.013960image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.801543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.948511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.773890image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.615624image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.495014image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.076812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.072538image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.890500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.671745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.653341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.474104image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.310444image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.311847image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.068167image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.864871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.010396image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.833572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.676545image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.547874image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.129969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.127375image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.946006image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.725094image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.704324image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.531473image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.360322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.358528image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.118630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.919174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.065520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.889157image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.731249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.600991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.183532image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.182744image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.999397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.775861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.762241image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.595758image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.411420image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.407339image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.165881image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.974123image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.123066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.944948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.788637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.653397image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.235715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.238560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.053572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.825599image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.815433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.664686image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.738042image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.455265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.216309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.028579image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.181081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.000108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.846080image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.722028image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.293218image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.296753image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.111125image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.098196image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.875345image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.732549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.792615image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.508942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.269110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.083970image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.242544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.058350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.905745image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.780764image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.350827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.358261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.169522image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.151482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.936017image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.795414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.845712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.560998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.323408image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.142443image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.303242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.121762image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.966333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.835105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.407819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.416010image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.226085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.202928image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.992409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.858090image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.897294image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.614382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.375492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.198558image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.361252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.180004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.028563image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.893360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:58.470296image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:40:59.478181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:00.287514image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:01.255663image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.047995image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:02.921931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:03.950364image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:04.668817image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:05.440948image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:06.258810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:07.422582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:08.240638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-03-01T09:41:09.096447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-03-01T09:41:12.815050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
host_listings_minimum_nightslatitudelog_days_since_last_reviewlog_host_listings_countlog_minimum_nightslog_nights_bookedlog_number_of_reviewslog_pricelog_reviews_per_monthlongitudeneighbourhoodpriceprice^2price^3price^4room_type
host_listings_minimum_nights1.000-0.181-0.1340.7090.617-0.269-0.2710.118-0.2700.2370.1990.1180.1180.1180.1180.118
latitude-0.1811.0000.064-0.186-0.0930.0710.1290.0800.089-0.5210.6710.0800.0800.0800.0800.148
log_days_since_last_review-0.1340.0641.000-0.193-0.0840.1830.252-0.0280.078-0.0750.157-0.028-0.028-0.028-0.0280.126
log_host_listings_count0.709-0.186-0.1931.0000.156-0.278-0.2140.038-0.1520.2960.2330.0380.0380.0380.0380.219
log_minimum_nights0.617-0.093-0.0840.1561.000-0.179-0.2740.135-0.3250.1380.1640.1350.1350.1350.1350.166
log_nights_booked-0.2690.0710.183-0.278-0.1791.0000.028-0.1150.042-0.0790.095-0.115-0.115-0.115-0.1150.095
log_number_of_reviews-0.2710.1290.252-0.214-0.2740.0281.000-0.1090.882-0.1880.128-0.109-0.109-0.109-0.1090.036
log_price0.1180.080-0.0280.0380.135-0.115-0.1091.000-0.1280.1910.1671.0001.0001.0001.0000.381
log_reviews_per_month-0.2700.0890.078-0.152-0.3250.0420.882-0.1281.000-0.1690.115-0.128-0.128-0.128-0.1280.103
longitude0.237-0.521-0.0750.2960.138-0.079-0.1880.191-0.1691.0000.5740.1910.1910.1910.1910.104
neighbourhood0.1990.6710.1570.2330.1640.0950.1280.1670.1150.5741.0000.0290.0000.0000.0000.217
price0.1180.080-0.0280.0380.135-0.115-0.1091.000-0.1280.1910.0291.0001.0001.0001.0000.069
price^20.1180.080-0.0280.0380.135-0.115-0.1091.000-0.1280.1910.0001.0001.0001.0001.0000.000
price^30.1180.080-0.0280.0380.135-0.115-0.1091.000-0.1280.1910.0001.0001.0001.0001.0000.000
price^40.1180.080-0.0280.0380.135-0.115-0.1091.000-0.1280.1910.0001.0001.0001.0001.0000.000
room_type0.1180.1480.1260.2190.1660.0950.0360.3810.1030.1040.2170.0690.0000.0000.0001.000

Missing values

2025-03-01T09:41:09.982249image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-01T09:41:10.066957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

neighbourhoodlatitudelongituderoom_typepricelog_days_since_last_reviewlog_reviews_per_monthlog_number_of_reviewslog_pricelog_minimum_nightslog_host_listings_countlog_nights_bookedhost_listings_minimum_nightsprice^2price^3price^4
1930infrequent41.79359-87.70345Private room462.0496060.6627582.2097831.6627580.0000000.4771210.0413930.0000002116973364477456
5588North Center41.95803-87.69214Entire home/apt120-1.000000-1.000000-1.0000002.0791810.3010300.0000002.4534710.000000144001728000207360000
599Logan Square41.92654-87.72505Entire home/apt1462.5989000.2304492.0004342.1643530.3010300.0000002.2674060.000000213163112136454371856
778Rogers Park42.00451-87.66203Entire home/apt1352.1792640.1038041.8267232.1303340.8450980.0000002.4655320.000000182252460375332150625
1509South Shore41.76867-87.56926Private room222.0685570.0644581.6138421.3424230.0000000.3010301.6637010.00000048410648234256
3660Bridgeport41.84030-87.65903Entire home/apt1182.0648320.1139431.3031962.0718820.3010300.3010302.5328820.090619139241643032193877776
766North Center41.94629-87.68011Entire home/apt1793.221179-0.8538720.3222192.2528530.4771210.4771212.5612210.2276453204157353391026625681
4018Near North Side41.89502-87.62791Entire home/apt130-1.000000-1.000000-1.0000002.1139431.4771212.3117541.3242823.414741169002197000285610000
2416Bridgeport41.83363-87.65166Private room442.179264-0.0506101.3636121.6434530.4771210.0000002.4410660.0000001936851843748096
4429Logan Square41.92595-87.69130Entire home/apt1102.634578-0.1870870.8512582.0413930.4771210.0000002.5624120.000000121001331000146410000
neighbourhoodlatitudelongituderoom_typepricelog_days_since_last_reviewlog_reviews_per_monthlog_number_of_reviewslog_pricelog_minimum_nightslog_host_listings_countlog_nights_bookedhost_listings_minimum_nightsprice^2price^3price^4
2709infrequent41.92027-87.77840Private room1152.712734-0.4814860.7853302.0606980.3010300.602060-1.0000000.181238132251520875174900625
3418Near North Side41.89163-87.63800Entire home/apt109-1.000000-1.000000-1.0000002.0374262.0791810.698970-1.0000001.453285118811295029141158161
1082Logan Square41.92309-87.68304Entire home/apt702.0417870.3560262.0457141.8450980.3010300.0000002.4534710.000000490034300024010000
4185Near West Side41.88340-87.64307Entire home/apt4002.621280-0.4814860.4913622.6020600.3010300.7781512.5624120.2342471600006400000025600000000
1356Avondale41.93312-87.70809Private room1392.503927-0.0132281.5453072.1430150.0000000.0000002.4084100.000000193212685619373301041
187West Town41.90669-87.68283Entire home/apt1142.6749530.3159702.1989322.0569050.3010300.0000002.5624120.000000129961481544168896016
3228East Garfield Park41.87980-87.70136Entire home/apt792.1007150.6314441.9498781.8976270.6020600.4771212.5392020.287256624149303938950081
2192North Center41.94383-87.68014Entire home/apt1282.0722500.4638931.9090212.1072100.6020600.0000001.3242820.000000163842097152268435456
638Lake View41.95045-87.65558Entire home/apt1252.778224-0.7958800.4913622.0969100.0000000.0000002.5624120.000000156251953125244140625
5690Logan Square41.92068-87.71599Entire home/apt1062.0174510.3222190.3222192.0253060.6020600.9030902.4473130.543714112361191016126247696

Duplicate rows

Most frequently occurring

neighbourhoodlatitudelongituderoom_typepricelog_days_since_last_reviewlog_reviews_per_monthlog_number_of_reviewslog_pricelog_minimum_nightslog_host_listings_countlog_nights_bookedhost_listings_minimum_nightsprice^2price^3price^4# duplicates
0Loop41.87723-87.62901Entire home/apt150-1.0-1.0-1.02.1760911.4771212.3117541.8457183.4147412250033750005062500002
1Near North Side41.89502-87.62791Entire home/apt152-1.0-1.0-1.02.1818441.4771212.3117541.8518703.4147412310435118085337948162
2Near West Side41.88306-87.65131Entire home/apt98-1.0-1.0-1.01.9912261.4771212.3117540.0413933.4147419604941192922368162